Abstract
Background:
Paliperidone Extended Release OROS (ER) is a new atypical antipsychotic for the treatment of schizophrenia. The objective is, based on a previously published model, to analyze the clinical and economic effects of Paliperidone ER in a Spanish setting compared to olanzapine oral and aripiprazole.
Methods:
An existing discrete event simulation model was adapted to reflect the treatment of schizophrenia in Spain in terms of costs, resource use, and treatment patterns. Inputs for the model were derived from clinical trial data, literature research, database analysis and interviews with local clinical experts. The time horizon is 5 years and Spanish discount rate was applied. Outputs include direct medical costs and Quality Adjusted Life-Years (QALYs). Extensive sensitivity analyses were carried out to assess the robustness of the results, using ordinary least squares analysis and cost-effectiveness scatter plots.
Results:
The results show that the mean incremental QALYs (95% CI) compared to olanzpine is 0.033 [−0.143, 0.304] and compared to aripiprazole 0.029 [−0.107, 0.300]. The corresponding mean incremental costs and corresponding confidence intervals are −€1425 [−€10,247, €3084] and −€759 [−€10,479, €3404], respectively. The probability that paliperidone ER is cost-saving and health gaining compared to olanzapine and aripiprazole is 76% and 72%, respectively. Paliperidone ER was estimated to have 80% and 81% probability of being cost-effective compared to olanzapine at a willingness to pay of €20,000 and €30,000 and 73% and 74% compared to aripiprazole, respectively.
Limitations:
Some of the modeled inter-relationships had to be based on expert opinion due to a lack of information. Also, foreign sources for the disutility of adverse events had been used due to a lack of Spanish data. Prolactin-related side-effects, indirect costs, and potential compliance advantages of paliperidone ER were not considered. It is unlikely that these limitations affected the conclusions.
Conclusion:
Based on differences in drug acquisition costs, side-effects, and risk of relapse, the model predicts that, in the Spanish healthcare setting, paliperidone ER dominates oral olanzapine and aripiprazole, with a probability of 76% and 72%, respectively.
Introduction
Schizophrenia is a debilitating chronic psychiatric illness with no definitive cure. It typically starts in late adolescence/early adulthood and has considerable impact on the patient and the patient’s environment, in terms of morbidity, mortality, human suffering and societal costsCitation1. According to Oliva-Moreno et al.Citation2 two regional studies estimate the prevalence of schizophrenia to be 0.6–0.8%. This would imply that currently ∼300,000 persons suffer from schizophrenia in Spain. The same study estimates the total direct medical cost associated with schizophrenia at €1044 million per year in 2002Citation2.
For the treatment of schizophrenia a large number of pharmacological options (known as antipsychotic medications) are available. These will not cure the disease, but they will reduce the symptoms and the number of relapses, slowing down the progression of disease and reducing the need for hospitalization. Antipsychotics can be sub-divided into two categories: the conventionals or first generation antipsychotics, starting to be introduced from the 1950s onwards (among others, haloperidol, flupentixol, perphenazine, and zuclophentixol), and the atypicals, or second generation antipsychotics, from the 1990s onwards (among others, risperidone, olanzapine, and quetiapine). A new atypical antipsychotic, called Paliperidone ER Extended-Release OROS (ER) (Invega, Janssen-Cilag, Titusvill, NJ) has been launched recently. Paliperidone ER was developed to improve patient compliance by inducing fewer side-effects, and an easier dosing profile due to the absence of titration needs and the once daily regimenCitation3–6. Moreover, based on a recent National Institute Clinical Excellence (NICE) report it seems that paliperidone ER is expected to reduce the number of relapses compared to olanzapine and aripiprazoleCitation7.
The objective of this report is to assess the potential clinical and economic effects of paliperidone ER as compared to olanzapine and aripiprazole. Results will be generated using a health economic model and will be discussed in terms of cost-effectiveness ratios, along with a number of more clinically relevant outcomes, such as the number of relapses and the time spent in certain treatment locations.
Methods
An existing DES model previously described by Heeg et al.Citation8 and othersCitation9–11 was adapted to reflect the treatment of schizophrenia in Spain in terms of treatment patterns, costs, and resource use. This adaptation was carried out based on literature research and expert interviews. Indirect costs are not considered, only direct medical costs. The model will be described briefly in this section, focusing on Spanish specific inputs and the parameters that differ between the compared medications: paliperidone ER, aripiprazole, and oral olanzapine.
Treatment schedule
The model compares paliperidone ER to the most prescribed branded oral atypical in Spain; olanzapine and to the most recently introduced oral atypical aripiprazole. After this initial treatment, patients can be switched to another antipsychotic (see ). For a fair comparison the differences between the considered treatments ought to be restricted to initial treatment only. Therefore, patients on either treatment were assumed to face a similar probability of receiving a certain medication for second and third line treatment, once discontinued on the prior treatment. Patients that enter the model are not necessarily treatment-naïve. The model selects the second and third line medications based on their relative market shares among the atypicals in terms of average daily doses (ADDs) sold (see ). The model ensures that patients do not receive the same treatment in both 2nd and 3rd treatment line.
Figure 1. Treatment schedule for comparison with oral olanzapine and aripiprazole; LAR = long acting risperidone.
Modeling mechanism
shows the modeling mechanism. The model simulates a patient’s history using both time-independent (i.e., gender, severity type, age) and time-dependent variables (which are presented in ).
Figure 2. Modeling mechanism.
The DES model simulates 50,000 patients in each treatment arm who suffer from multiple relapses, over a time period following a relapse which necessitates the involvement of a psychiatrist. This number of patients was chosen to ensure model stability, i.e., to mitigate potential sampling errors. The scores on the Positive And Negative Syndrome Scale (PANSS) are associated with the treatment given to the patient, with compliance and the duration of relapses. The longer the time between relapses, the higher a patient’s PANSS scoreCitation12. Patients can be either compliant, partially compliant, or non-compliant. A compliant patient experiences a 20% PANSS score reduction during episodes and a 5% reduction between relapsesCitation13–16, whereas it was assumed a partially compliant patient experiences half that effect.
Effectiveness measured by Quality Adjusted Life-Years (QALYs) is explained by the PANSS and by the occurrence of side-effects. The association between PANSS and quality of life is estimated on the basis of the relation found by Lenert et al.Citation17 To estimate the impact of the different side-effects on the QALY, a multiplicative model is used. In this model, the parameters associated with weight gain are 0.959Citation17, with tardive dyskinesia 0.857Citation17, with diabetes 0.81Citation18,Citation19, with EPS 0.888Citation17, and with sedation/somnolence 0.905Citation20.
PANSS is an indicator of the severity of the disease and therefore also affects the treatment location. The decision to switch from treatment setting is based on the current location, whether the patient is perceived to present a risk of causing harm to him/herself or society, and whether the patient is able to take care of him/herself. These patient characteristics depend on the PANSS. Costs depend mainly on the treatment location, but also on the cost of the medication. Main outputs are the predicted incremental (discounted) costs (in euros) and effects (in QALYs) over a time period of 3–5 years. Following national guidelines for Spain a 3% discount rate was applied.
Model input
Side-effect profiles for the drugs considered in this analysis are provided in . Side-effects include weight gain, somnolence/sedation, diabetes mellitus, tardive dyskinesia, extrapyramidal symptoms (EPS), and agranulocytosis. These have been obtained from clinical trials.
Table 1. Side-effect profiles of considered antipsychotics.
In the original model by Heeg and colleaguesCitation8–11, relapse risks were based on Csernansky et al.Citation27. NICE has recently conducted a mixed treatment comparisonCitation7. They found a hazard ratio between olanzapine and paliperidone ER of 1.26 and a hazard ratio between aripiprazole and paliperidone ER of 1.81Citation7 (see ). These relative differences have been applied to the Csernansky et al.Citation27 data (in which no differentiation between treatments was made) to obtain relapse risks for the current model. In addition, a differentiation exists between first and second generation antipsychotics in terms of relapse risk, PANSS reduction, and side-effect profileCitation15,Citation27,Citation34–38 and long and short action formulationsCitation39–41. These latter differentiations, however, have minimal impact on the current comparison as it does not include a first generation antipsychotic or a long-acting formulation.
Table 2. Hazard ratios for risk of relapse profiles relative to paliperidoneCitation7.
Compliance rates across treatment locations are outlined in . These were based on expert opinion and describe the probability a patient is fully compliant. Patients that are not fully compliant were assumed to be partially compliant or non-compliant at a 2:3 ratio.
Table 3. Compliance rates (probability that a patient is fully compliant) by treatment location.
Drug acquisition costs, location costs, side-effect costs, and monitoring costs are outlined in . The location prices were derived from Vazquez-Polo et al.Citation42 and Boletin Oficial de MurciaCitation43. Patients experiencing weight gain attended the general practitioner (GP) twice a year and a dietetic nurse 3-times a yearCitation1. Patients developing diabetes attended the GP twice a year and would receive one glucose analyticCitation1. In addition, they would receive treatment with metformin at a price of €0.14 per dayCitation1. Patients having EPS had an additional psychiatrist visit and attended the GP once a yearCitation1. Also they would receive biperiden 6 mg a day at a price of €0.18 a day. Corresponding costs for GP, nurse, and psychiatrist visits and a glucose analytic were based on values reported by the Spanish Ministry of HealthCitation1.
Table 4. Modeled healthcare costs.
Monitoring costs were obtained from expert input. All prices have been updated to 2010 prices using the Spanish consumer price indices provided by the Organization of Economic Co-operation and Development (http://stats.oecd.org/wbos/).
Sensitivity analysis
Two sets of scenario analyses were conducted. The first investigates the impact of other reported hospitalization durations of 15.6 and 35 days, compared to 21 in the base case, on the outputs. The second set of sensitivity analysis considered the disutilities associated with side-effects. As these were not obtained from Spanish-specific sources, their relevance to the current patient population remains uncertain. To address this issue, two extreme scenarios were tested; one in which the disutilities were non-existent (i.e. no impact on quality-of-life) and one in which the effect on quality-of life was doubled.
To assess the joint sensitivity of the results, a multivariate probabilistic sensitivity analysis of 1000 runs was carried out. Based on the incremental costs and effects generated by these sensitivity analyses, scatter plots and acceptability curves are made. Clearly, the most important parameters in these analyses are the ones that differ between the comparators, e.g., side-effects and time between relapses. Side-effects were included in the probabilistic sensitivity analysis by a beta distribution, which is defined by two parameters; alpha and beta. Alpha is the number of patients with a side-effect and beta the number of patients without the side-effect. The difference in time between relapses was included by distribution over the scale parameter of the Weibull distribution which is used to estimate the time between relapses. Also the hazard ratios reflecting the relative difference in risk of relapse between paliperidone ER and oral olanzapine and aripiprazole were included and simulated by a normal distribution, reflecting the uncertainty margins reported in the NICE reportCitation7. Other parameters included in the PSA were the difference in PANSS reduction by a triangular distribution with a mean of 10%, a minimum of −2%, and a maximum of 22%. Compliance was simulated by a normal distribution with a mean as presented in and a standard error which is 10% of the meanCitation8–11. The scale parameter is varied by 10%. The location costs, which were simulated by a log-normal distribution with a mean as presented in and a standard error of 10% of the meanCitation8–11.
Results
The 5-year results in terms of costs, resource use, and effects for paliperidone ER, olanzapine, and aripiprazole are presented in . It seems that paliperidone ER reduces the number of relapses with 0.06 and 0.14 years over a 5-year period compared to oral olanzapine and aripiprazole, respectively. This, together with its favorable side-effect profile, results in the expectation that paliperidone ER increases the patients QALY by 0.033 and 0.029 compared to both comparators, respectively. Due to the lower risk of relapse and that patients treated with paliperidone ER have low monitoring costs for side-effects results in incremental discounted savings of €1425 compared to olanzapine and a €759 saving compared to aripiprazole over a 5-year period.
Table 5. Results base case analysis.
In the univariate sensitivity analyses excluding the impairing effect of adverse events on quality-of-life, QALY gains of paliperidone ER compared to olanzapine and aripiprazole increased to 0.062 and 0.049, respectively if the effect of side effects on quality of life was doubled. The length-of-stay of hospitalization on the outcomes did not change the result of dominance, i.e. cost saving and more effective.
Multivariate probabilistic analyses
The results of the multivariate probabilistic sensitivity analyses are presented in a scatter plot (). The scatter plot shows the incremental costs and effects of the 1000 runs per comparison. The mean incremental QALY compared to olanzapine is 0.033 [−0.143, 0.304] and compared to aripiprazole 0.029 [−0.109, 0.300]. The corresponding incremental costs and confidence intervals are −€1425 [−€10,247, €3084] and −€759 [−€10,479, €3404], respectively. Compared to olanzapine, paliperidone ER has a 76.2%, 8.8%, 7.0%, 14.3% probability to be cost-saving and more effective, cost-saving and less effective, more costly and more effective, and more costly and less effective, respectively (see ). The corresponding probabilities compared to aripiprazole are 71.7%, 1.0%, 4.0%, and 23.3%.
Figure 3. Scatter plot.
The acceptability curve displayed in shows the probability that paliperidone ER is cost-effective compared to olanzapine and aripiprazole across different willingness-to-pay threshold levels. The latter is expressed as the maximum additional cost one would be willing to pay for an additional QALY gained. shows that paliperidone ER has 79.9% and 81.1% probability of being cost-effective against olanzapine at WTP of €20,000 and €30,000 and 73.2% and 73.6% against aripiprazole, respectively.
Figure 4. Acceptability curve.
Discussion
To demonstrate the cost-effectiveness of paliperidone ER in the Spanish setting a discrete event simulation model was used which simulates individual patients over a 5-year period while comparing paliperidone ER with olanzapine and aripiprazole.
The acceptability curve shows that paliperidone ER has 79.9% and 81.1% probability of being cost-effective against olanzapine at WTP of €20,000 and €30,000 and 73.2% and 73.6% against aripiprazole, respectively. The probability that paliperidone ER is health gaining and cost-saving compared to olanzapine and aripiprazole is 76.2% and 71.7%, respectively.
The major source for the uncertainty is the variability in relapse hazard ratio between paliperidone ER and olanzapine and aripiprazole. This data comes from a mixed treatment comparison from NICE. It should be noted that the potential correlation between the relapse risks of the atypicals could not be included as this was not reported in the NICE data. As a result, the uncertainty surrounding the hazard ratios between paliperidone ER and its comparators (and thus the uncertainty in the scatter plot and acceptability curve) is probably over-estimated due to a likely positive correlation between these estimates. However, this type of data was not available to the modelers.
A fundamental driver of incremental QALYs is the disutilities associated with adverse events. Due to the lack of Spanish-specific data these were obtained from foreign sources, making their applicability to the current analysis uncertain. In an extreme scenario ignoring the effect of adverse events on quality-of-life, QALY gains almost diminished to 0, but leaving the cost advantage intact. If the effect on quality-of-life would be doubled, QALY gains would also be approximately twice as high. The effect in reality will probably lie somewhere in between both scenarios.
The model findings seem in line with other studies published on the cost-effectiveness of Paliperidone ER in Greece and the USCitation44–46. These papers, however, used a different methodology to come to similar conclusions on paliperidone ER. Regarding external validity of the model results, Oliva-Moreno et al.Citation2 report €1044 million total medical costs for schizophrenia in Spain in 2002. This would be €1220 million at current price levels (adjusted for consumer price indices as found at http://stats.oecd.org/wbos/). With an approximate prevalence of 0.6–0.8%Citation2 and an estimated population of 44 million people, this would give annual total costs of €3465–€4620 per schizophrenic patient. The model estimates total discounted costs of ∼€30,000 per patient over 5 years, which translates to €6000 per patient per year. The model slightly over-estimates the 2002 figure, but changes in treating schizophrenia patients in Spain may explain these differences.
Moreover, Mason et al.Citation51 estimated that patients spend ∼40% of their time in relapse. The model predicts patients spend about 2 out of 5 years in relapse, which is exactly 40%.
The limitations of the model have been described in detail elsewhereCitation8–11. Ideally, the model would have been based solely on published data. Unfortunately, not all of the included inter-relationships could be based on published data due to a lack of long-term studies, making relying on expert opinion unavoidable. However, the drivers for the incremental effects are not based on expert opinion but on systematic reviews on side-effectsCitation21,Citation27–38, and the difference in relapse hazard rates reported by the NICECitation7. Expert opinion mainly has been used to validate the model according to the Spanish treatment setting.
Moreover, despite the fact that sexual dysfunction and other potentially prolactin-related side-effects are known to occur amongst schizophrenia patients, little is known about the exact inter-relationship between individual antipsychotics, prolactin levels, and potentially prolactin-related side-effects. In the literature no consensus has been reached as the data is inconsistent, often limited to small sample sizes and expressed in terms of a wide variety of outcome measures, making it difficult to draw any quantitative conclusions that could be included in the current modelCitation47–50. Nevertheless, the incidence of potentially prolactin-related side-effects (such as amenorrhea, gynecomastia, and sexual dysfunction) was not significantly different between placebo and paliperidone ER. Hence, based on the findings of the paliperidone ER clinical trialsCitation50, excluding this side-effect can result in two different effects. If the incidence of prolactin-related side-effects for the comparators is equal to placebo (and thus to Paliperidone ER) it is not expected to result in a model bias. If on the other hand the incidence of prolactin-related side-effects for the comparators is higher than placebo (and thus to paliperidone ER) the model is conservative in terms of generated QALY gains by paliperidone ER.
Indirect costs associated with work productivity losses were excluded from the analysis as the payer perspective was considered. However, including indirect costs would likely result in further cost-savings for paliperidone ER. Paliperidone has less relapse time, during which patients are at higher risk of incurring productivity losses.
A possible benefit for paliperidone ER that is not taken into account is that possibly one or two psychiatrist visits can be avoided (less incremental costs) if patients start medication with paliperidone ER, due to the fact that determining the optimal dose (titration) takes less time. Also, what is not included is the potential advantage of paliperidone ER on improved patient compliance by inducing fewer side-effects.
Conclusion
Based on the model results it seems that in the Spanish healthcare setting paliperidone ER dominates olanzapine and aripiprazole with a probability of 76.2% and 71.7%, respectively.
Transparency
Declaration of funding
This work was financially supported by Janssen-Cilag Spain. The researchers were free to choose the methodology in all stages of the study and were entitled to publish the results in a scientific journal of their choice.
Declaration of financial/other interests
MT and BH have disclosed that they are employees of Pharmerit, a company that received an unrestricted grant from Janssen-Cilag to help conduct this study. LS and FC have no relevant financial relationship to disclose. EB has disclosed that he has received grants and consultant fees from Pfizer and has been affiliated with Janssen-Cilag. JB has disclosed that he has received grants from Pfizer and Roche, and is on the speakers’ bureau of Adamed, AstraZeneca, and Janssen. BG has disclosed that she is an employee of Janseen-Cilag.
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